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Fix unit tests for background detectors as Things

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This commit is contained in:
Julian Stirling 2026-01-13 19:49:34 +00:00
parent 3e8874188e
commit 6b97d2da44
5 changed files with 51 additions and 116 deletions
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4
tests/hardware_specific_tests/picamera2/test_calibration.py
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@ -19,7 +19,7 @@ def test_calibration(picamera_test_env):
# Tuning should start the same as the server is loading with no settings.
assert picamera_thing.default_tuning == picamera_thing.tuning
# The background detector isn't ready as there is no background image.
assert not picamera_thing.background_detector_status.ready
assert not picamera_thing.active_detector.ready
# Run full auto calibrate
picamera_client.full_auto_calibrate()
@ -31,7 +31,7 @@ def test_calibration(picamera_test_env):
# The default should be unchanged
assert picamera_thing.default_tuning == original_default
assert picamera_thing.background_detector_status.ready
assert picamera_thing.active_detector.ready
def test_tuning_is_persistent():

143
tests/unit_tests/test_background_detectors.py
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@ -7,15 +7,15 @@ import re
import numpy as np
import pytest
from pydantic import BaseModel
from openflexure_microscope_server.background_detect import (
import labthings_fastapi as lt
from labthings_fastapi.testing import create_thing_without_server
from openflexure_microscope_server.things.background_detect import (
BackgroundDetectAlgorithm,
ChannelBlankError,
ChannelDeviationLUV,
ChannelDistributions,
ColourChannelDetectLUV,
ColourChannelDetectSettings,
MissingBackgroundDataError,
_chunked_stds,
)
@ -55,56 +55,45 @@ def test_bg_detect_base_class():
If initialised as is it should raise not implemented error.
"""
with pytest.raises(NotImplementedError):
BackgroundDetectAlgorithm()
create_thing_without_server(BackgroundDetectAlgorithm)
def test_partial_base_classes():
"""Create a partial classes and check they raise the correct errors."""
"""Create a partial class and check it raises the correct errors."""
class BadAlgo1(BackgroundDetectAlgorithm):
"""Only has a settings model so it cannot initialise."""
class BadAlgo(BackgroundDetectAlgorithm):
"""Can initialise. Other properties and methods error."""
settings_data_model = ColourChannelDetectSettings
display_name: str = lt.property(default="Bad Algorithm", readonly=True)
bad_algo = create_thing_without_server(BadAlgo)
with pytest.raises(NotImplementedError):
BadAlgo1()
class BadAlgo2(BackgroundDetectAlgorithm):
"""Only has a background model so it cannot initialise."""
background_data_model = ChannelDistributions
bad_algo.ready
with pytest.raises(NotImplementedError):
BadAlgo2()
class BadAlgo3(BackgroundDetectAlgorithm):
"""Has both models, intalises by cannot run set_background or image_is_sample."""
settings_data_model = ColourChannelDetectSettings
background_data_model = ChannelDistributions
bad_algo3 = BadAlgo3()
bad_algo.settings_ui
with pytest.raises(NotImplementedError):
bad_algo3.set_background(background_image)
bad_algo.set_background(background_image)
with pytest.raises(NotImplementedError):
bad_algo3.image_is_sample(background_image)
bad_algo.image_is_sample(background_image)
def test_colour_channel_luv(background_image, sample_image):
"""Test measuring if a sample is background."""
cc_luv = ColourChannelDetectLUV()
cc_luv = create_thing_without_server(ColourChannelDetectLUV)
# No background data so it is not ready and will error if image_is_sample is called.
assert not cc_luv.status.ready
assert not cc_luv.ready
with pytest.raises(MissingBackgroundDataError):
cc_luv.image_is_sample(background_image)
# Set the background
cc_luv.set_background(background_image)
# Now it is ready
assert cc_luv.status.ready
assert cc_luv.ready
sample, message = cc_luv.image_is_sample(background_image)
assert not sample
assert "0.0%" in message
@ -116,7 +105,7 @@ def test_colour_channel_luv(background_image, sample_image):
assert 49.8 < float(match.group(1)) < 50.2
# Require 75% coverage
cc_luv.settings = ColourChannelDetectSettings(min_sample_coverage=75.0)
cc_luv.min_sample_coverage = 75.0
sample, message = cc_luv.image_is_sample(sample_image)
# No longer detected as a sample.
@ -127,69 +116,6 @@ def test_colour_channel_luv(background_image, sample_image):
assert 49.8 < float(match.group(1)) < 50.2
def test_colour_channel_luv_save_load(background_image, sample_image):
"""Get settings and data as dicts, and creating new instance using these dicts.
This is how the camera will load/save settings from/to disk.
"""
cc_luv = ColourChannelDetectLUV()
cc_luv.set_background(background_image)
# Check types for background data
assert cc_luv.background_data_model is ChannelDistributions
assert isinstance(cc_luv.background_data, cc_luv.background_data_model)
# Change Settings
cc_luv.settings = ColourChannelDetectSettings(min_sample_coverage=10.0)
setting_dict = cc_luv.settings.model_dump()
data_dict = cc_luv.background_data.model_dump()
# Remove the old detector so we don't accidentally use it!
del cc_luv
# Create a new instance
cc_luv2 = ColourChannelDetectLUV()
assert not cc_luv2.status.ready
# Load settings and channels from dictionary as the camera will do on init.
cc_luv2.settings = setting_dict
cc_luv2.background_data = data_dict
# Now should be ready to use
assert cc_luv2.status.ready
assert cc_luv2.settings.min_sample_coverage == 10.0
sample, _ = cc_luv2.image_is_sample(sample_image)
assert sample
# Remove the 2nd detector so we don't accidentally use it!
del cc_luv2
# One final test that None can be set explicitly to background data as this will
# happen if loading with background detect not saved.
cc_luv3 = ColourChannelDetectLUV()
assert not cc_luv3.status.ready
# Load settings and channels from dictionary as the camera will do on init.
cc_luv3.settings = setting_dict
cc_luv3.background_data = None
# Still not ready
assert not cc_luv3.status.ready
def test_colour_channel_luv_load_bad_data():
"""Check a type error is thrown on bad data input."""
class WrongModel(BaseModel):
"""Using a different BaseModel as this is most likely to cause confusion."""
prop1: int = 8
prop2: str = "foo"
cc_luv = ColourChannelDetectLUV()
with pytest.raises(TypeError):
cc_luv.settings = WrongModel()
with pytest.raises(TypeError):
cc_luv.background_data = WrongModel()
def create_patchwork_image(magnitude=3, blank_channels=None):
"""Create a patchwork image, with known stds per chunk.
@ -239,7 +165,7 @@ def test_chunked_stds_with_precomputed_chunk_stds():
def test_channel_deviation_luv_set_background(mocker):
"""Test set_background takes the median of each channel, and errors for blank channels."""
cd_luv = ChannelDeviationLUV()
cd_luv = create_thing_without_server(ChannelDeviationLUV)
# Patch RGB to LUV so or we don't know what the STDs should be
mocker.patch("cv2.cvtColor", side_effect=lambda img, _method: img)
@ -252,7 +178,7 @@ def test_channel_deviation_luv_set_background(mocker):
# Do a somewhat verbose checking for clarity
for channel in range(3):
# Saved std
channel_std = cd_luv.background_data.standard_deviations[channel]
channel_std = cd_luv.background_stds[channel]
# Expected median
channel_median = np.median(expected_stds[:, :, channel])
# If the median is above the minimum allowed then it should be returned
@ -270,21 +196,21 @@ def test_channel_deviation_luv_set_background(mocker):
def test_channel_deviation_luv_image_is_sample(background_image, mocker):
"""Check image_is_sample reports the result from get_sample_coverage."""
cd_luv = ChannelDeviationLUV()
cd_luv = create_thing_without_server(ChannelDeviationLUV)
# No background data so it is not ready and will error if image_is_sample is called.
assert not cd_luv.status.ready
assert not cd_luv.ready
with pytest.raises(MissingBackgroundDataError):
cd_luv.image_is_sample(background_image)
cd_luv.settings.min_sample_coverage = 20
cd_luv.min_sample_coverage = 20
cd_luv.get_sample_coverage = mocker.Mock(return_value=10)
is_sample, message = cd_luv.image_is_sample(background_image)
assert not is_sample
assert message == r"only 10.0% sample"
# Reduce the min coverage
cd_luv.settings.min_sample_coverage = 9
cd_luv.min_sample_coverage = 9
is_sample, message = cd_luv.image_is_sample(background_image)
assert is_sample
@ -293,34 +219,29 @@ def test_channel_deviation_luv_image_is_sample(background_image, mocker):
def test_channel_deviation_luv_get_sample_coverage(background_image, mocker):
"""Check _get_sample_coverage returns the values expected."""
cd_luv = ChannelDeviationLUV()
cd_luv = create_thing_without_server(ChannelDeviationLUV)
# Create fake chunked STD data where each channel is the numbers 0 -> 31.5 in 0.5
# steps
grid = np.arange(0, 32, 0.5).reshape(8, 8)
fake_stds = np.stack([grid, grid, grid], axis=-1)
mocker.patch(
"openflexure_microscope_server.background_detect._chunked_stds",
"openflexure_microscope_server.things.background_detect._chunked_stds",
return_value=fake_stds,
)
# Create fake background
cd_luv.background_data = ChannelDistributions(
means=[0, 0, 0], standard_deviations=[1.1, 1.1, 1.1]
)
cd_luv.background_stds = [1.1, 1.1, 1.1]
# Get sample coverage with channel tolerance of 7. Checking each channel for the
# numbers below 7.7. There are 16 out of 64. So 75% should be sample
cd_luv.settings.channel_tolerance = 7
cd_luv.channel_tolerance = 7
assert cd_luv.get_sample_coverage(background_image) == 75
# This is unchanged if two channels have larger background values.
cd_luv.background_data = ChannelDistributions(
means=[0, 0, 0], standard_deviations=[1.6, 1.6, 1.1]
)
cd_luv.background_stds = [1.6, 1.6, 1.1]
assert cd_luv.get_sample_coverage(background_image) == 75
# But coverage increases if any channels has a lower background value.
cd_luv.background_data = ChannelDistributions(
means=[0, 0, 0], standard_deviations=[1.6, 0.6, 1.1]
)
cd_luv.background_stds = [1.6, 0.6, 1.1]
assert cd_luv.get_sample_coverage(background_image) == 85.9375
# Returns to 75% if that channel is empty
fake_stds[:, :, 1] = 0

9
tests/unit_tests/test_simulated_camera.py
View file

@ -10,6 +10,7 @@ from hypothesis import strategies as st
import labthings_fastapi as lt
from openflexure_microscope_server.things.background_detect import ChannelDeviationLUV
from openflexure_microscope_server.things.camera import simulation
from openflexure_microscope_server.things.camera.simulation import SimulatedCamera
from openflexure_microscope_server.things.stage.dummy import DummyStage
@ -20,7 +21,11 @@ from ..shared_utils.lt_test_utils import LabThingsTestEnv
@pytest.fixture
def test_env() -> LabThingsTestEnv:
"""Yield a test environment with the Simulated Camera and Dummy Stage."""
thing_conf = {"camera": SimulatedCamera, "stage": DummyStage}
thing_conf = {
"camera": SimulatedCamera,
"stage": DummyStage,
"bg_channel_deviations_luv": ChannelDeviationLUV,
}
with LabThingsTestEnv(things=thing_conf) as env:
yield env
@ -181,4 +186,4 @@ def test_simulation_cam_calibration(camera):
assert camera.calibration_required
camera.full_auto_calibrate()
assert not camera.calibration_required
assert camera.background_detector_status.ready
assert camera.active_detector.ready